Web usage mining refers to an application of data mining techniques to determine user access patterns from web usage data. Web usage mining typically involves tracking browsing activities using a variety of measures such as individual mouse clicks and time spent on a portion of a webpage in order to have a user's browsing footprint available at the web server. Generally, website mining results include features such as number of page views, number of unique users, browser and operating system information, user's website view pattern, widely viewed pages, browser and operating system information.
The ability to track the website usage information is useful to assess the impact of website content which can result in enhancement of business opportunities and metrics for cost benefits analysis. Tracking usage patterns is also useful for identifying which content on the website is being heavily used (and therefore should be kept) and which content is not being heavily used (and may be a candidate for archiving). In addition, it helps to improve the website design by rearranging the content on the pages so that the end users have a more convenient experience while exploring the website. In addition, website usage statistics can also keep track of how much storage space the web pages on a website are taking, which content on the website is important, and the level of activity for particular website pages or websites.
The enhancement of business opportunities, for example, include increasing the number of visits on the website. One way of increasing the number of visits is by increasing number of loyal users or by converting first time visitors to loyal users. The number of first time visitors can be increased by monitoring the web usage patterns and suggesting certain web content to first time visitors. Accordingly, it is desired to discover and act upon the various patterns of website usage to provide a more enjoyable experience to its first time visitors, which also help to increase the chances of converting these visitors into loyal users.